Abstract: A thermal detection method comprises steps of providing a rotation device, disposing a thermal sensor on the rotation device, rotating the rotation device, and using the thermal sensor to detect a temperature of an object without contacting the object. A thermal detecting system comprises a rotation device and a thermal sensor disposed on the rotation device for detecting a temperature of an object without contacting the object.

Abstract: A thermal detection method comprises steps of providing a rotation device, disposing a thermal sensor on the rotation device, rotating the rotation device, and using the thermal sensor to detect a temperature of an object without contacting the object. A thermal detection system comprises a rotation device and a thermal sensor disposed on the rotation device for detecting a temperature of an object without contacting the object.

Abstract: An alarm analysis method capable of multi-purpose function. A plurality of efficiency indices are defined, including statistical-data-configuration, data-set, background-alarm-rate, peak-alarm-rate, active-alarm-distribution, bad-actors-identification, and alarm-report indices. A data warehouse is created according to the efficiency indices and using an online analytical processing method. A plurality of user interfaces are created according to the data warehouse and analysis results. The data warehouse is accessed using the user interfaces to retrieve the analysis results.

Abstract: An alarm analysis method capable of multi-purpose function. A plurality of efficiency indices are defined, comprising statistical-data-configuration, data-set, background-alarm-rate, peak-alarm-rate, active-alarm-distribution, bad-actors-identification, and alarm-report indices. A data warehouse is created according to the efficiency indices and using an online analytical processing method. A plurality of user interfaces are created according to the data warehouse and analysis results. The data warehouse is accessed using the user interfaces to retrieve the analysis results.

Abstract: A method for calculating key performance indexes. The method comprising defining running indexes for a heat exchanger of a chiller, obtaining an outlet temperature of output matter of the heat exchanger according to the running indexes, at least comprising load temperature, load current, inlet temperature of cooling matter, outlet temperature of the cooling matter, and inlet temperature of the output matter, obtaining a performance index according to the inlet and outlet temperatures of the output matter and the load current of the heat exchanger, obtaining a predicted performance index according to the inlet temperature of the output matter, a predicted outlet temperature of the output matter, and the load current, obtaining a real performance index according to the inlet temperature of the output matter, real outlet temperature of output matter, and the load current, and obtaining a key performance index according to the predicted and real performance indexes.

Abstract: A real-time monitoring system and method for processes or tools. Historical data for processes or tools is first collected and abnormal data then analyzed using statistical analysis. At least one control chart model is designated according to the analysis result, and model parameters and linking settings related to control chart models are stored in a database. Next, a real-time monitoring model is created by merging control chart models, using model-creating technologies, according to abnormal-state causes, the model parameters, and the linking settings, and several monitoring models are then merged as a real-time monitoring model. Finally, operating states of the processes or tools are displayed using the real-time monitoring model according to real-time data or the historical data stored in the database.

Abstract: A real-time monitoring system and method for processes or tools. Historical data for processes or tools is first collected and abnormal data then analyzed using statistical analysis. At least one control chart model is designated according to the analysis result, and model parameters and linking settings related to control chart models are stored in a database. Next, a real-time monitoring model is created by merging control chart models, using model-creating technologies, according to abnormal-state causes, the model parameters, and the linking settings, and several monitoring models are then merged as a real-time monitoring model. Finally, operating states of the processes or tools are displayed using the real-time monitoring model according to real-time data or the historical data stored in the database.